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Project developed using Data Mining, Machine Learning and Data Visualization techniques to extract information and make predictions based on positional data

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ClaudioPoli/Indoor-movements-forecasting-model

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Indoor movements forecasting model

Project developed using Data Mining, Machine Learning and Data Visualization techniques to extract information and make predictions based on positional data.

Thesis work consisting in the acquisition and manipulation of a structured space-time database on which different operations have been performed. The first concerns a graphical analysis of the data using a dashboard; subsequently an algorithm was implemented to perform pattern recognition and finally a recurrent neural network, in particular an LSTM, was implemented to perform prediction operations.

  • Programming languages: Python, HTML, SQL
  • Libraries: Pandas, Keras, Tensorflow, Plotly, Matplotlib
  • Algorithms: PrefixSpan

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Project developed using Data Mining, Machine Learning and Data Visualization techniques to extract information and make predictions based on positional data

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